The present invention relates generally to detection of abnormally hot rail car wheel bearing surfaces, and more specifically to signal processing of infrared signals emitted by hot surfaces of such bearings and surrounding structures.
Railcars riding on wheel trucks occasionally develop overheated bearings. The overheated bearings may eventually fail and cause costly disruption to rail service. Many railroads have installed wayside hot bearing detectors (HBDs) that view the bearings and surrounding structure surfaces as a rail car passes, and generate an alarm upon detection of an abnormally hot surface. One of the commonly used techniques includes employing sensors in the HBDs that sense heat generated by the bearing surfaces. For example, pyroelectric sensors may be used that depend upon the piezoelectric effect. However, such sensors can be susceptible to noise due to mechanical motion of the railcars. Such noise may result from so-called microphonic artifacts, and can complicate the correct diagnosis of hot bearings, or even cause false positive readings. In general, false positive readings, although false, nevertheless require stopping a train to verify whether the detected bearing is, in fact, overheating, leading to costly time delays and schedule perturbations.
Accordingly, an improved system and method that would address the aforementioned issues is needed.